I planned to analyse some data with several ANOVAs (I have many different dependent variables), but much of the data violates the ANOVA assumptions, so they require Welch's ANOVA or the non-parametric Kruskal-Wallis test instead.
Using SPSS, I generated effect sizes (partial eta squared) and observed power values for the data which I analysed using an ANOVA.
I calculated estimated omega squared as an effect size for the Welch's ANOVAs using this formula:
est. omega squared = DFbetweensjcts(F-1) / (DFbetweensjcts(F-1)+N)
I calculated eta squared as an effect size for the Kruskal-Wallis test using this formula:
eta squared = (Kruskal-Wallis chi-square value) / (N-1)
The problem is, I am unsure how to calculate observed power for the Welch's ANOVA or Kruskal-Wallis test. Is it possible to do this? If so, how?
Also, I found the formulae to calculate omega squared and eta squared somewhere online, so I'm a little unsure whether these are correct.
Any help would be really appreciated!
Using SPSS, I generated effect sizes (partial eta squared) and observed power values for the data which I analysed using an ANOVA.
I calculated estimated omega squared as an effect size for the Welch's ANOVAs using this formula:
est. omega squared = DFbetweensjcts(F-1) / (DFbetweensjcts(F-1)+N)
I calculated eta squared as an effect size for the Kruskal-Wallis test using this formula:
eta squared = (Kruskal-Wallis chi-square value) / (N-1)
The problem is, I am unsure how to calculate observed power for the Welch's ANOVA or Kruskal-Wallis test. Is it possible to do this? If so, how?
Also, I found the formulae to calculate omega squared and eta squared somewhere online, so I'm a little unsure whether these are correct.
Any help would be really appreciated!